A survey on time-sensitive resource allocation in the cloud continuum

Saravanan Ramanathan, Nitin Shivaraman, Seima Suryasekaran, Arvind Easwaran, Etienne Borde, Sebastian Steinhorst

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Artificial Intelligence (AI) and Internet of Things (IoT) applications are rapidly growing in today's world where they are continuously connected to the internet and process, store and exchange information among the devices and the environment. The cloud and edge platform is very crucial to these applications due to their inherent compute-intensive and resource-constrained nature. One of the foremost challenges in cloud and edge resource allocation is the efficient management of computation and communication resources to meet the performance and latency guarantees of the applications. Numerous research studies have been carried out to address this intricate problem. In this paper, the current state-of-the-art resource allocation techniques for the cloud continuum, in particular those that consider time-sensitive applications, are reviewed. Furthermore, we present the key challenges in the resource allocation problem for the cloud continuum, a taxonomy to classify the existing literature and the potential research gaps.

Original languageEnglish
Pages (from-to)241-255
Number of pages15
JournalIT - Information Technology
Volume62
Issue number56
DOIs
StatePublished - 16 Dec 2021

Keywords

  • Cloud computing
  • Edge computing
  • Internet of Things
  • Resource allocation and scheduling

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